PROTECT -- A Deployed Game Theoretic System for Strategic Security Allocation for the United States Coast Guard

Authors

  • Bo An University of Southern California
  • Eric Shieh University of Southern California
  • Milind Tambe University of Southern California
  • Rong Yang University of Southern California
  • Craig Baldwin United States Coast Guard
  • Joseph DiRenzo United States Coast Guard
  • Ben Maule United States Coast Guard
  • Garrett Meyer United States Coast Guard

DOI:

https://doi.org/10.1609/aimag.v33i4.2401

Keywords:

Game Theory, Security, Applications, Stackelberg Games

Abstract

While three deployed applications of game theory for security have recently been reported, we as a community of agents and AI researchers remain in the early stages of these deployments; there is a continuing need to understand the core principles for innovative security applications of game theory. Towards that end, this paper presents PROTECT, a game-theoretic system deployed by the United States Coast Guard (USCG) in the port of Boston for scheduling their patrols. USCG has termed the deployment of PROTECT in Boston a success, and efforts are underway to test it in the port of New York, with the potential for nationwide deployment.


PROTECT is premised on an attacker-defender Stackelberg game model and offers five key innovations. First, this system is a departure from the assumption of perfect adversary rationality noted in previous work, relying instead on a quantal response (QR) model of the adversary's behavior --- to the best of our knowledge, this is the first real-world deployment of the QR model. Second, to improve PROTECT's efficiency, we generate a compact representation of the defender's strategy space, exploiting equivalence and dominance. Third, we show how to practically model a real maritime patrolling problem as a Stackelberg game. Fourth, our experimental results illustrate that PROTECT's QR model more robustly handles real-world uncertainties than a perfect rationality model. Finally, in evaluating PROTECT, this paper for the first time provides real-world data: (i) comparison of human-generated vs PROTECT security schedules, and (ii) results from an Adversarial Perspective Team's (human mock attackers) analysis.

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Published

2012-12-21

How to Cite

An, B., Shieh, E., Tambe, M., Yang, R., Baldwin, C., DiRenzo, J., Maule, B., & Meyer, G. (2012). PROTECT -- A Deployed Game Theoretic System for Strategic Security Allocation for the United States Coast Guard. AI Magazine, 33(4), 96. https://doi.org/10.1609/aimag.v33i4.2401

Issue

Section

Articles